1. Field of the Invention
The present invention relates to a channel equalizer that performs channel equalization by determining filter coefficients corresponding to near and far ghost images, and by dividing the near ghost images and far ghost images in a vestigial side band (VSB) transmission system of a high definition television (HDTV).
2. Description of the Related Art
A VSB transmission system transmits a training sequence signal from a transmitting part to a receiving part prior to transmitting a data signal in order to compensate in the receiving part for an error that may occur when the data is transmitted from the transmitting part through a transmission channel.
A channel equalizer is used in the receiving part of the VSB transmission system for compensating for linear channel distortion such as tilts or ghost images generated when signals pass from the transmission channel to the receiver and for transmitting data from the transmitting terminal to the receiving terminal. The channel equalization acts as a filter to reduce channel distortion generated during transmission.
Most important in channel equalization is how to calculate a filter coefficient. One method for channel equalization calculates a filter coefficient by using the training sequence signal transmitted from the transmitting terminal.
FIG. 1 is a block diagram of a conventional channel equalizer. The conventional channel equalizer includes a filter coefficient renewal part 12 which takes as input data, V.sub.n and a filtered signal I.sub.n received from outside of the channel equalizer and outputs a filter coefficient C.sub.n. A finite impulses response filter (FIR) 11 filters the input signal V.sub.n received from outside of the channel equalizer by means of the filter coefficient C.sub.n, output by the filter coefficient renewal part 12, and then outputs the filtered signal In.
The FIR filter 11 that has 256 taps formed of filter coefficients C.sub.0 to C.sub.255, filters the input signal V.sub.n by combining linearly the present input signal and the previous input values. The input signal V.sub.n is filtered in response to filter coefficients C.sub.0 to C.sub.255, sequentially inputted from the filter coefficient renewal part 12.
The filter coefficient renewal part 12 determines the filter coefficient C.sub.n, using the received input signal V.sub.n and the filtered signal I.sub.n, output by the FIR filter 11.
The conventional channel equalizer feeds back the output signal I.sub.n of the channel equalizer to the filter coefficient renewal part 12, which then calculates the filter coefficient C.sub.n, using the signal I.sub.n and the signal V.sub.n. Channel equalization is performed by renewing the filter coefficient C.sub.n from C.sub.0 to C.sub.255 according to the number of taps.
The least mean square (LMS) algorithm is expressed by the following formula (1): EQU C.sub.n+1 =C.sub.n +.DELTA.E.sub.n V.sub.n-k ( 1)
C.sub.n, C.sub.n+1, .DELTA., and E.sub.n designate, respectively, a previous filter coefficient, a filer coefficient that is now to be obtained, a constant, and a value of error.
The value of error is R.sub.2 -I.sub.n in the case of a blind channel equalizer, and is otherwise a value I.sub.T -I.sub.n, where I.sub.n is the output of the channel equalizer and I.sub.T is the training sequence signal.
V.sub.n-k is a value of the input of the channel equalizer and becomes I.sub.T if the channel equalizer is using the training sequence signal as input. Accordingly, the filter coefficient is expressed as: EQU C.sub.n+1 =C.sub.n +.DELTA.(I.sub.n -I.sub.n) I.sub.T ( 2)
FIG. 2 is a detailed circuit diagram of the filter coefficient renewal part 12 of FIG. 1.
The filter coefficient renewal part 12 comprises a slicer 12-1 which converts the filtered signal I.sub.n, output by the FIR filter 11, to a predetermined transmission level; an adder 12-2 which calculates the difference between the signal from the slicer 12-1 and the filtered signal I.sub.n, received from the FIR filter 11, and outputs the difference as a value of error; a multiplier 12-3 which multiplies the output value of error by a constant .DELTA.; an adder 12-4 which adds the signal output by the multiplier 12-3 and the previous filter coefficient to find a new filter coefficient C.sub.n+1.
The conventional filter coefficient renewal part 12 converts the signal I.sub.n, output by the channel equalizer, into a predetermined transmission level through the slicer 12-1, and determines the difference between the output signal of the slicer 12-1 and the output signal I.sub.n of the channel equalizer. The filter coefficient renewal part 12 outputs this difference as a value of error.
The value of error output is multiplied by a constant .DELTA., between 0 and 1, and the reduced value of error is added to the previous filter coefficient C.sub.n in the adder 12-4 and is output to the FIR filter 11 as a new filter coefficient C.sub.n+1.
Accordingly, the FIR filter 11 performs the channel equalization using the filter coefficient C.sub.n+1 received from the filter coefficient renewal part 12. In the channel equalization, the convergent speed is the most important factor, when using the LMS algorithm. The convergent speed of the channel equalizer depends on how rapidly the filter coefficient is renewed. Since the conventional channel equalizer sequentially computes all the filter coefficient up to the number of taps of the filter coefficient, the channel equalizer takes a long time to converge.